In this paper, we propose an inverse kinematics optimization layer that leverages the strengths of both optimization and regression for end-to-end 3D human pose and shape estimation, namely IKOL.

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      @inproceedings{
      zhang2023ikol,
      title={IKOL: Inverse kinematics optimization layer for 3D human pose and shape estimation via Gauss-Newton differentiation},
      author={Juze Zhang and Ye Shi and Yuexin Ma and Lan Xu and Jingyi Yu and Jingya Wang},
      booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},
      year={2023},
      };